A hierarchical based ensemble classifier for behavioral malware detection using machine learning

MJ Hussain, A Shaoor, S Baig… - … on Applied Sciences …, 2022 - ieeexplore.ieee.org
Malwares are increasingly threatening the security and confidentiality of data. Therefore, the
issues related to malware detection are gaining interest among the researchers. In this …

Malicious pdf detection based on machine learning with enhanced feature set

SY Yerima, A Bashar, G Latif - 2022 14th International …, 2022 - ieeexplore.ieee.org
PDF is one of the most popular document file formats due to its flexibility, platform
independence and ability to embed different types of content. Over the years, PDF has …

[PDF][PDF] A Deep Learning Based Approach for Malware Detection and Classification

OE Taylor, PS Ezekiel, DJS Sako - iJournals: International Journal …, 2021 - researchgate.net
Vindictive programming or malware represents a significant source of security concern in
this cutting-edge age as computer clients, companies, and governments witness an …

Malware detection using image-based features and machine learning methods Görüntü tabanli özelliklerden ve makine öǧrenmesi yöntemlerinden faydalanilarak …

A Güngör, İ DOĞRU, N BARIŞÇI… - Journal of the Faculty of …, 2023 - avesis.gazi.edu.tr
© 2023 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved. As Android devices
occupy more of people's lives, they have also become a target of malicious software. It is …

Obfuscated Malware Memory Detection Employing Lazy Instance Based Learner Algorithm Based On Manhattan Distance Function

H Sabah Talabani… - Passer Journal of …, 2024 - passer.garmian.edu.krd
Malware is a severe threat to the network and host system security. It is frequently the
primary cause of many events, such as Distributed Denial-of-Service attacks (DDoS), spam …

AI-HydRa: Advanced hybrid approach using random forest and deep learning for malware classification

S Yoo, S Kim, S Kim, BB Kang - Information Sciences, 2021 - Elsevier
The extremely diffused architecture of the Internet enables the propagation of malware and
presents a significant challenge for the development of defenses against such malware …

[PDF][PDF] Performance evaluation of machine learning algorithms for detection and prevention of malware attacks

EG Dada, JS Bassi, YJ Hurcha… - IOSR Journal of Computer …, 2019 - academia.edu
Malware is any type of program that is intended to wreak havoc to the computer system and
network. Examples of malware are bot, ransomware, adware, keyloggers, viruses, trojan …

Machine learning based improved malware detection schemes

P Priyadarshan, P Sarangi, A Rath… - 2021 11th International …, 2021 - ieeexplore.ieee.org
In recent years, cyber security has become a challenging task to protect the networks and
computing systems from various types of digital attacks. Therefore, to preserve these …

Detection and Classification of Malware for Cyber Security using Machine Learning Algorithms

S Judy, R Khilar - 2023 Eighth International Conference on …, 2023 - ieeexplore.ieee.org
The threat of malware to information security is one that keeps growing. However, the
Windows operating system faces a very high level of unintended security risk. System …

[PDF][PDF] A chi-square-based decision for real-time malware detection using PE-file features

M Belaoued, S Mazouzi - Journal of Information Processing …, 2016 - koreascience.kr
The real-time detection of malware remains an open issue, since most of the existing
approaches for malware categorization focus on improving the accuracy rather than the …